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Adaptive Modelling, Estimation and Fusion from Data [Hardcover]

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Item Number 230236  
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Item description for Adaptive Modelling, Estimation and Fusion from Data by Chris Harris...

In a world of almost permanent and rapidly increasing electronic data availability, techniques of filtering, compressing, and interpreting this data to transform it into valuable and easily comprehensible information is of utmost importance. One key topic in this area is the capability to deduce future system behavior from a given data input.

This book brings together for the first time the complete theory of data-based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data-based modelling, new concepts including extended additive and multiplicative submodels are developed and their extensions to state estimation and data fusion are derived. All these algorithms are illustrated with benchmark and real-life examples to demonstrate their efficiency.

Chris Harris and his group have carried out pioneering work which has tied together the fields of neural networks and linguistic rule-based algortihms. This book is aimed at researchers and scientists in time series modeling, empirical data modeling, knowledge discovery, data mining, and data fusion.

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Item Specifications...

Pages   323
Est. Packaging Dimensions:   Length: 9" Width: 6.94" Height: 0.94"
Weight:   1.45 lbs.
Binding  Hardcover
Release Date   Jun 20, 2002
Publisher   Springer
ISBN  3540426868  
ISBN13  9783540426868  

Availability  64 units.
Availability accurate as of Oct 28, 2016 06:31.
Usually ships within one to two business days from La Vergne, TN.
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More About Chris Harris

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Product Categories

1Books > Calendars > Arts
2Books > Special Features > New & Used Textbooks > Computer Science & Information Systems > Artificial Intelligence
3Books > Subjects > Computers & Internet > Computer Science > Artificial Intelligence > Computer Mathematics
4Books > Subjects > Computers & Internet > Computer Science > Artificial Intelligence > General
5Books > Subjects > Computers & Internet > Computer Science > Artificial Intelligence > Human Vision & Language Systems
6Books > Subjects > Computers & Internet > Computer Science > Artificial Intelligence > Neural Networks
7Books > Subjects > Computers & Internet > Computer Science > Artificial Intelligence > Theory of Computing
8Books > Subjects > Computers & Internet > General
9Books > Subjects > Computers & Internet > Programming > Algorithms > Fuzzy Logic
10Books > Subjects > Professional & Technical > Professional Science > Mathematics > Pure Mathematics > Set Theory
11Books > Subjects > Science > Mathematics > Pure Mathematics > Set Theory

Reviews - What do customers think about Adaptive Modelling, Estimation and Fusion from Data?

Where is the data ?  May 26, 2003
While i do not deny the contribution at providing a more or less complete treatment of neurofuzzy techniques for data modeling, i'm still wondering where the non-theoretical chapters dealing with how to cope with real data with these techniques are hidden. The few examples in the book are mostly artificial and very limited in their scope. i'm not sure people dealing with data have an interest at reading this book, it's more about neurofuzzy techniques than data modelling.

The book edited by Schwefel, Weneger and Weinert entitled "Advances in computational intelligence" published by Springer emphasizes a lot more on fuzzy techniques based on real data although it does not discuss the "neuro" part of "neuro-fuzzy" techniques.

Still this book is not bad from a theoretical neuro-fuzzy perspective, but since these techniques are aimed at dealing with real data, i would have hoped a much better treatment of the practical aspects, which it fails to provide.


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